With the influx of money, attention and entrepreneurial energy, there is a massive amount of innovation taking place to solve data centric problems (such as the high cost of collecting, cleaning, curating, analyzing, maintaining, predicting) in new ways.

There are two distinct patterns in data-centric innovation:

Disruptive innovation like predictive search which brings a very different value proposition to tasks like discover, engage, explore and buy and/or creates new markets!!

Sustaining innovation like mobile dashboards, visualization or data supply chain management which improves self service and performance of existing products and services.

With either pattern the managerial challenge is moving from big picture strategy to day-to-day execution. Execution of big data or data-driven decision making requires a multi-year evolving roadmap around toolset, skillset, dataset, and mindset.

British Airways “Know Me” Project

British Airways (BA) has focused on competitiveness via customer insight. It has petabytes of customer information from its Executive Club loyalty program and its website. BA decided to put customer big data to work in its Know Me program. The goal of the program is to understand customers better than any other airline, and leverage customer insight accumulated across billions of touch points to work.

BA’s Know Me program is using data and applying it to customer decision points in following ways:

Personal recognition—This involves recognizing customers for being loyal to BA, and expressing appreciation with targeted benefits and recognition activities

Personalization — based on irregular disruptions like being stuck on a freeway due to an accident – A pre-emptive text message… We are sorry that you are missing your flight departure to Chicago. Would you like a seat on the next one at 5:15PM. Please reply Yes or No.

Service excellence and recovery—BA will track the service it provides to its customers and aim to keep it at a high level. Given air travel constant problems and disruptions, BA wants to understand what problems its customers experience, and do its best to recover a positive overall result

Offers that inspire and motivate—BA’s best customers are business travelers who don’t have time for irrelevant offers, so Know Me program analyzes customer data to construct relevant and targeted “next best offers” for their consideration.

The information to support these objectives is integrated across a variety of systems, and applied in real-time customer interactions at check-in locations and lounges. Even on BA planes, service personnel have iPads that display customer situations and authorized offers. Some aspects of the Know Me program have already been rolled out, while others are still under development.

The Need for New Data Roadmaps

New IT paradigms (cloud resident apps, mobile apps, multi-channel, always-on etc.) are creating more and more complex integration landscapes with live, “right-now” and real-time data. With data increasingly critical to business strategy, the problems of poor quality data, fragmentation, and lack of lineage are also taking center stage.

The big change taking place in the application landscape: application owners of the past expected to own their data. However, applications of the future will leverage data – a profound change that is driving the data-centric enterprise. The applications of the future need one “logical” place to go that provides the business view of the data to enable agile assembly.

Established and startup vendors are racing to fill this new information management void. The establish vendors are expanding on this current enterprise footprint by adding more features and capabilities. For example, the Oracle BI stack (hardware – databases – platform – prebuilt content) illustrates the data landscape changes taking place from hardware to mobile BI apps. Similar stack evolution is being followed by SAP AG, IBM, Teradata and others. The startup vendors typically are building around disruptive technology or niche point solutions.

To enable this future of information management, there are three clusters of “parallel” innovation waves: (1) technology/infrastructure centric; (2) business/problem centric; and (3) organizational innovation.

IBM summarize this wave of innovation in this Investor Day slide:

Data Infrastructure Innovation

Data sources and integration — Where does the raw data come from?

Data aggregation and virtualization- Where it stored and how is it retrieved?

Clean high quality data — How does the raw data get processed in order to be useful?

Even in the technology/infrastructure centric side there are multiple paths of disruptiveinnovation that are taking along different technology stacks shown below.

Defining Business Analytics

What is Business Analytics? Business Analytics is the intersection of business and technology, offering new opportunities for a competitive advantage. Business analytics unlocks the predictive potential of data analysis to improve financial performance, strategic management, and operational efficiency.

What is BI? BI is the "computer-based techniques used in spotting, digging-out, and analyzing 'hard' business data, such as sales revenue by products or departments or associated costs and incomes. Objectives of BI implementations include (1) understanding of a firm's internal and external strengths and weaknesses, (2) understanding of the relationship between different data for better decision making, (3) detection of opportunities for innovation, and (4) cost reduction and optimal deployment of resources." (Business Dictionary). Most widely used BI tool is Microsoft Excel.
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What is Big Data? Big data refer to data scenarios that grow so large (petabytes and more) that they become awkward to work with using traditional database management tools. The challenge stems from data volume + flow velocity + noise to signal conversion. Big data is spawning new tools that are mix of significant processing power, parallelism and statistical, machine learning, or pattern recognition techniques
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Corporate performance management software and performance management concepts, such as the balanced scorecard, enable organizations to measure business results and track their progress against business goals in order to improve financial performance.
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Data visualization tools, include mashups, executive dashboards, performance scorecards and other data visualization technology, is becoming a major category.
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BI platforms provide a range of capabilities for building analytical applications. Examples are Oracle OBIEE, SAP Business Objects 4.0. There are many choices and combinations of BI platforms, capabilities and use cases as well as many emerging BI technologies such as in memory analytics, interactive visualization and BI integrated search. The idea of standardizing on one supplier for all of one’s BI capabilities is difficult to do. Increasingly, standardization and more about managing a portfolio of tools used for a set of capabilities and use cases.
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Data integration tools and architectures in support of BI continue to evolve. Extract-Transfer-Load (ETL) tools make up a big segment of this category in addition to data mapping tools. Organizations must now support a range of delivery styles, latencies, and formats.
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BI is about "sense and respond." Analytics is about "anticipate and shape" models.

About

Business Analytics 3.0 blog is meant for decision makers and managers who are trying to make sense of the rapidly changing technology landscape and build next generation solutions. It is aimed at helping business decision makers navigate the "Raw Data -> Aggregate Data -> Intelligence -> Insight -> Decisions" chain.